摘要： 提出一种基于区域小波统计特征的遥感图像融合方法，对多光谱图像的I分量与直方图匹配后的高分辨率图像进行小波变换融 合。对分解后的低频分量采用加权平均的融合规则，高频分量则根据其区域的小波系数特征，采用基于区域方差匹配度的融合规则。对 SPOT多光谱图像和高分辨率图像进行融合实验，并利用信息熵和相关系数对融合结果进行客观评价与比较分析。仿真实验结果表明，基于区域小波统计特征的融合方法能达到较好的融合效果。

关键词: 直方图匹配, 小波变换, 区域特征, 方差匹配度, 图像融合

Abstract: This paper proposes a remote sensing image fusion method based on regional wavelet statistical features. Wavelet decomposition is done between the I-component of multi-spectrum image and the high-resolution image after histogram-matching. For the low frequency component, this method uses a fusion rule of weighted average. And for the high frequency component, it uses regional variance-matching based on regional wavelet coefficient characteristics. The fusion experiment is carried out by the SPOT multi-spectrum image and high-resolution image. Entropy and correlation coefficient are used to judge and analyze the fusion results objectively. Simulation experimental results show that the proposed method can achieve better fusion effect.

Key words: histogram matching, wavelet transform, regional feature, variance matching, image fusion

中图分类号: 

• TP751